# About me .pull-left[ <img src="data:image/png;base64,#images/hello.jpg" width="400px" style="display: block; margin: auto;" /> .center[ my name is .large[Shaun Nielsen] ] * [
shaunnielsen.com.au](https://shaunnielsen.com.au) * [
@Shaunson26](https://github.com/Shaunson26) * [
shaunson26@gmail.com](mailto:shaunson26@gmail.com) ] .pull-right[ ### Experience **Data Science and Engineering Consultant** **R tutor** Applied Epi **Senior Data Analyst** - Government public health **Biostatistican** - Government public health **Postdoctural researcher** - Microbial ecology </br> </br> <div style="display: flex;align-items: center;justify-content: space-between"> <img src="data:image/png;base64,#images/NSW-logo-and-health-descriptor-large.png" width="100px" /> <img src="data:image/png;base64,#images/unsw.png" width="100px" /> <img src="data:image/png;base64,#images/applied-epi.png" width="100px" /> <img src="data:image/png;base64,#images/cnb-logo.png" width="100px" /> </div> ] --- # Course objective .center[.large[ Give you experience across the scientific data analysis pipeline using R and RStudio ]] <div class="figure" style="text-align: center"> <img src="data:image/png;base64,#images/course-data-science-process.png" alt="Image adapted from R for Data Science" width="70%" /> <p class="caption">Image adapted from R for Data Science</p> </div> -- .center[.large[ so you can continue to build a foundation and work independently (and collaboratively) ]] -- - Make using R less daunting - Ability to apply tasks from others resources (books, tutorials, etc) - Build a foundation for more complex applications - Troubleshoot common R and analysis problems --- # Learning - R is a skill <style type="text/css"> .practice-practice { position: absolute; bottom: 5%; right: 2%; width: 300px; } </style> .. like learning a new language or musical instrument - **Practice regularly** .. the more you do, the more you learn - **Repetition is key** .. repeatedly using commands and techniques solidifies understanding and improves retention - **Experiment and explore** .. try modifying code examples and exploring different functions. See what happens! - **Do not be afraid of making mistakes** .. helps you understand how R works. Do not get discouraged by errors. Search for solutions and learn from them </br> </br> -- This is a relatively **short course** - There is lots of information to cover - Goal is to **expose you broadly to topics** .. you **must** practice and repeat! - The timing between sessions (2 days / week for 2 weeks) give you time! .practice-practice[ <!-- --> ] --- # Course outline .pull-left[ ## Module 1 - first steps - Using R and RStudio - Coding basics - Data types and structures - R packages - Importing data ] -- .pull-right[ ## Module 2 - data manipulation - Manipulating and transforming data - Joining data - Reshaping data ] -- .pull-left[ ## Module 3 - data visualisation - Visualising data - Creating different plot types - Exporting plots ] -- .pull-right[ ## Module 4 -basic statistics - t-tests - ANOVA - Linear models ] --- # Course structure **Short lectures**: 5 - 20 min -- **Exercises**: 20 - 30 min -- - Simple responses .pull-left[ ``` r # Calculate the log of 4.5 _ ``` ] -- .pull-right[ ``` r # Calculate the log of 4.5 log(4.5) ``` ] -- - To more complex code .pull-left[ ``` r # Obtain the total cases and deaths by country # and year. There should not be any NA values covid %>% _ ``` ] -- .pull-right[ ``` r # Obtain the total cases and deaths by country # and year. There should not be any NA values covid %>% group_by(country) %>% summarise(total_cases = sum(cases), ...) ``` ] -- **Discussion of exercises**: 5 - 10 min -- **Small project**: Provided at the start of course and submitted within 1 week after the course. --- # Course dates and times We have **4 days** - 19, 21, 27 ad 29 May - 2 days / week over 2 weeks - Gives time for you to revise content and ask questions <br> A total of **13 hours** (14 including breaks) - 3.5 hours per day (3.25 hours + 15 min break time) - 9:30 a 13.00 <br> We will work through parts of modules and stop when necessary - 10 - 30 min per module sub-section --- # Course references - R for Data Science (book/online) - https://r4ds.hadley.nz/ - Introductory Statistics with R (book) - [link to pdf](https://www.academia.dk/BiologiskAntropologi/Epidemiologi/PDF/Introductory_Statistics_with_R__2nd_ed.pdf) - Environmental computing (online) - https://environmentalcomputing.net/ - The Edpidemiologist R hanbook (online) - [English](https://epirhandbook.com/en) / [Spanish](https://epirhandbook.com/es) <br> <br> .pull-left[ .pull-left[ <img src="data:image/png;base64,#images/rd4s.jpg" height="200px" style="display: block; margin: auto;" /> ] .pull-right[ <img src="data:image/png;base64,#images/intro-stats.png" height="200px" style="display: block; margin: auto;" /> ] ] .pull-right[ .pull-left[ <img src="data:image/png;base64,#images/epi-handbook.png" width="100%" style="display: block; margin: auto;" /> ] .pull-right[ <img src="data:image/png;base64,#images/env-comp.png" height="200px" style="display: block; margin: auto;" /> ] ] --- # Have you setup your computer? Open RStudio now ... - Installed **R**, **RStudio** and **git** - Started an RStudio project with the link - https://github.com/Shaunson26/r-for-scientific-research - **Open RStudio** using the `r-for-scientific-research.Rproj`. - You should be working within the course project throughout the course. <img src="data:image/png;base64,#images/rproject-started.png" width="100%" style="display: block; margin: auto;" /> --- # Downloading course content I will release module content sequentially. It can be download using the **git** panel and **pull** <img src="data:image/png;base64,#images/git-pull.png" style="display: block; margin: auto;" /> --- # Research field and R use survey I created a survey to capture information about your research field, data use and experience with R - https://forms.gle/VUGScKHPSLaKn28p8 - I will create a simple analysis with this data and share it with you during the course <img src="data:image/png;base64,#images/google-form.png" width="500px" style="display: block; margin: auto;" /> --- class: middle # Let's begin!